Sentiment Analysis of printed and social media using NLP

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Keywords:

RoBERTa, Web Scrapping, Positive, Negative, Neutral, Optical Character Recognition (OCR)

Abstract

During The pandemic many stores have changed their mode into online mode that is E-marketing and not only that because of this  much increase in online shopping it has become hard to trust which is a reliable product and which is not, to overcome these types of problems comments and star ratings help us a lot but the star rating cannot be accurate some people have misconception like 1 star for good 5 for bad.The comments which they post don’t have this type of ambiguity so if there is a model which can understand and analyse a huge number of comments and give a correct opinion then it will help a lot. This model will help us to understand human language and so the application can also be used on printed media whereby analysing the headlines we can come to know how a year, a month or a day went. Analysing various newspapers will help us to know which paper is imposing negative or positive or neutral thoughts on people.

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Published

2024-08-27

How to Cite

Govinda Patil, & Vivek Chaplot. (2024). Sentiment Analysis of printed and social media using NLP. Journal of Computational Analysis and Applications (JoCAAA), 33(2), 10–21. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/234

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